首页 > 过刊浏览>2018年第37卷第5期 >26-31. DOI:10.19464/j.cnki.cn32-1541/tm.2018.05.005
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一种新的电压偏差预测方法
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上海市科委地方能力建设计划项目(16020500900)


A Method of Short-term Voltage Deviation Forecasting
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    摘要:

    针对电压偏差预测难度大的问题,文中提出一种新的电压偏差预测方法。该方法包括主成分分析法(principal component analysis,PCA)降维、亲和力传播(affinity propagation,AP)聚类、反向传播(back propagation,BP)神经网络预测3步。通过PCA对数据进行降维,获得数据主成分;为了弥补传统聚类方法的不足,提高聚类效果,文中引入AP聚类提取与待预测点同类的历史数据;最后选择BP神经网络建立电压偏差预测模型。将文中方法应用于实际电压偏差数据,结果表明该方法预测结果平均相对误差为3.06%,优于传统BP神经网络预测模型以及BP神经网络结合PCA降维的预测模型。

    Abstract:

    This paper presents an accurate model to forecast voltage deviation with improved BP neural network,which concerns with the meteorological factors.The proposed method is a combination of PCA dimension reduction,AP clustering and BP neural network.The proposed method is successfully applied to actual data and the practical application results proved that the mean absolute percentage error (MAPE) of the proposed method is 3.06%,which is obviously better than that of other methods.

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王知芳,杨秀,潘爱强.一种新的电压偏差预测方法[J].电力工程技术,2018,37(5):26-31

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  • 收稿日期:2018-05-09
  • 最后修改日期:2018-06-27
  • 录用日期:2018-07-05
  • 在线发布日期: 2018-09-28
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